Elucidation of mu-Opioid Gene Structure: How Genetics Can Help Predict Responses to Opioids.
Elucidation of mu-Opioid Gene Structure: How Genetics Can Help Predict Responses to Opioids.
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DOI：
10.1016/j.eujps.2011.08.022
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发表时间：
2011-11-11
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阿片类药物是最常用和最有效的人类镇痛剂之一。迄今为止，阿片类镇痛药的临床获益尚未完全实现，原因是对阿片类药物的反应存在显著的个体差异、药物剂量不足以及不良事件发生率较高（高达66%）。因此，有必要确定介导阿片类药物治疗的个体反应的遗传和分子生物学机制。近年来的研究表明，μ阿片受体（OPRM 1）基因位点的遗传变异在个体间反应中起着重要作用。大多数的遗传关联研究都集中在A118 G多态性，它编码OPRM 1外显子1的非同义变化。除了A118 G多态性，另一个功能性SNP（rs 563649），它位于一个选择性剪接OPRM 1亚型（莫尔-1 K），已被确定。莫尔-1 k同种型编码6 TM OPRM 1同种型，其显示兴奋性而非抑制性细胞效应，这是典型7 TM同种型的特征。因此，6 TM亚型的刺激可能参与介导阿片依赖性痛觉过敏、耐受性和依赖性的分子机制。未来的临床和基础研究，旨在确定OPRM 1基因座内的功能性遗传变异，以及相关的分子机制，将导致更好地了解个体对阿片类药物治疗的反应，并最终开发新的药物治疗和诊断工具。
Opioid drugs are among the most commonly used and effective human analgesics. To date, the clinical benefits of opioid analgesics have not been fully realized due to substantial individual variations in the responses to opioids, insufficient drug dosing, and a high rate (up to 66%) of adverse events. As such, there is a substantial need to identify the genetic and molecular biological mechanisms that mediate individual responses to opioid therapy. Recent discoveries show that genetic variations in the μ-opioid receptor (OPRM1) gene locus play an essential role in inter-individual responses. The majority of genetic association studies have focused on the A118G polymorphism, which codes for a non-synonymous change in OPRM1 exon 1. In addition to the A118G polymorphism, another functional SNP (rs563649), which is located within an alternatively-spliced OPRM1 isoform (MOR-1K), has been identified. The MOR-1k isoform codes for 6TM OPRM1 isoforms that display excitatory rather than the inhibitory cellular effects, which are characteristic of the canonical 7TM isoforms. Thus, stimulation of the 6TM isoforms may engage the molecular mechanisms mediating opioid-dependent hyperalgesia, tolerance and dependence. Future clinical and basic studies that seek to identify the functional genetic variants within OPRM1 locus, and associated molecular mechanisms, will result in a better understanding of individual responses to opioid therapy and ultimately to the development new pharmacotherapeutics and diagnostic tools.